Modelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era

England has experienced a heavy burden of COVID-19, with multiple waves of SARS-CoV-2 transmission since early 2020 and high infection levels following the emergence and spread of Omicron variants since late 2021. In response to rising Omicron cases, booster vaccinations were accelerated and offered to all adults in England. Using a model fitted to more than 2 years of epidemiological data, we project potential dynamics of SARS-CoV-2 infections, hospital admissions and deaths in England to December 2022. We consider key uncertainties including future behavioural change and waning immunity and assess the effectiveness of booster vaccinations in mitigating SARS-CoV-2 disease burden between October 2021 and December 2022. If no new variants emerge, SARS-CoV-2 transmission is expected to decline, with low levels remaining in the coming months. The extent to which projected SARS-CoV-2 transmission resurges later in 2022 depends largely on assumptions around waning immunity and to some extent, behaviour, and seasonality.

Seroprevalence estimates from 1st December 2020 onwards are not used for model fitting and are plotted in blue on top of the modelled cumulative number of seroconversions over time. Coloured lines and shaded areas show medians, 50% and 90% interquantile ranges from the fitted model. COVID-19 deaths data was provided by the UK Health Security Agency (UKHSA) and hospital admissions, hospital and ICU bed occupancy data was provided by NHS England. These data sources are unpublished and not publicly available, but are closely aligned with the UK Government's COVID-19 dashboard 3 . PCR prevalence data was obtained from the Office for National Statistics' COVID-19 Infection Survey (ONS-CIS) 4 . Seroprevalence data was obtained from the UK Biobank 5 , REACT-2 study 6 and from the ONS-CIS 4,7 . ICU = intensive care unit. NHS = National Health Service. confidence intervals for PCR prevalence and seroprevalence estimates. Seroprevalence estimates from 1st December 2020 onwards are not used for model fitting and are plotted in blue on top of the modelled cumulative number of seroconversions over time. Coloured lines and shaded areas show medians, 50% and 90% interquantile ranges from the fitted model. COVID-19 deaths data was provided by the UK Health Security Agency (UKHSA) and hospital admissions, hospital and ICU bed occupancy data was provided by NHS England. These data sources are unpublished and not publicly available, but are closely aligned with the UK Government's COVID-19 dashboard 3 . PCR prevalence data was obtained from the Office for National Statistics' COVID-19 Infection Survey (ONS-CIS) 8 . Seroprevalence data was obtained from the UK Biobank 9 , REACT-2 study 6 Table S4), measured booster vaccination uptake relative to second dose uptake as of April 2022 10 , and 20% seasonality introduced from 1st April 2021. Full details about the assumptions for each scenario are given in Table 1. Table: the total number of COVID-19 infections, hospital admissions, and deaths, between 1st May and 31st December 2022, shown to 3 significant figures. The 6-month scenario is marked with an asterisk (*) and corresponds to the basecase scenario. Booster vaccination rollout in England started in September 2021, initially targeted to at-risk individuals and individuals aged 50 years and above, 6 months after their previous COVID-19 vaccination. In December 2021 following increasing numbers of Omicron cases, the booster vaccination rollout was accelerated and extended to all individuals aged 18 years and above, with the minimum recommended gap between the previous vaccination and the booster dose shortened to 3 months 11 . Later in December 2022, booster vaccinations were also recommended for individuals aged 16 and 17 years old, at least 3 months following completion of their primary COVID-19 vaccination course 12  infections (thousands), hospital admissions and deaths are simulated until December 2022, with different assumptions used for the rate that immunity (conferred from vaccination and following a prior infection) wanes (see Table S4). The shaded areas and solid lines show the 50% and 90% interquantile ranges, and the median for each time point, while the dashed line shows a single sample trajectory. The vertical dotted lines denote the end of model fitting and the beginning of model projections. Full details about the assumptions for each scenario are given in Table 1. Tables: the total  number of COVID-19 Table 2).

Supplementary Table 4 -Waning immunity scenarios.
Modelling assumptions for the rates of waning immunity. All rates shown here correspond to the rates at which individuals with some form of immunity (either from vaccination or from a prior infection) lose their immunity and return to a fully susceptible disease state.
Default waning values are used for the majority of scenarios, including the basecase (see main manuscript Table  1). The high waning scenario assumes a non-zero rate of waning for individuals with second-dose / second-dose + boosted levels of protection (wva2, wvb2), whereas the central scenario assumes no waning for these categories of individuals. The very high waning scenario assumes the same loss of protection as the high waning scenario but in half the amount of time.  We referred to a number of studies looking at the level of protection against reinfection with SARS-CoV-2 15 . An unweighted mean across these studies finds approximately 85.74% protection against reinfection with SARS-CoV-2 after 27.76 weeks. When individuals in the model wane, they lose all remaining protection against SARS-CoV-2 outcomes of all types. Our central assumptions therefore assume that the rate at which individuals lose all their protection is slower than that at which reinfections might occur. *We used vaccine-specific measured reductions in protection against hospitalisation over 20 weeks from Andrews et al. 16 Supplementary

dVa1 / dVb1
The duration that individuals have first-dose levels of vaccine protection before transitioning to second-dose levels. Note that we assume a 28-day delay between individuals receiving their first-dose and moving into first-dose levels of protection, and an equivalent 14-day delay before individuals reach second-dose efficacy. These duration assumptions take those delays into account.

= 21.5 -28 + 14
Then, The average delay between first and second vaccine doses was 21.5 days prior to 26th January 2021 when the JCVI updated their guidance 28 on dosing schedules, extending the maximum recommended dosing gap. Following this, the average delay was measured as more than 71 days, using data from October 2021.

dVa2 / dVb2
The duration that individuals have second-dose levels of vaccine protection before receiving a booster vaccine or transitioning to a second-dose + waned state. Note that we assume a 14-day delay before individuals reach second-dose efficacy. These duration assumptions take those delays into account.

(+28 days) as for infection
Overall protection against hospitalisation for AstraZeneca dose 1 Lopez Bernal et al.

(+28 days)
Overall protection against infection for Pfizer dose 2 Hall et al.